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External Validation of Two Models to Predict Delirium in Critically Ill Adults Using Either the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist for Delirium Assessment

Wassenaar, Annelies RN, CCRN, PhD1; Schoonhoven, Lisette PhD, FEANS2,3; Devlin, John W. PharmD4,5; van Haren, Frank M. P. MD, PhD6,7,8; Slooter, Arjen J. C. MD, PhD9; Jorens, Philippe G. MD, PhD10; van der Jagt, Mathieu MD, PhD11; Simons, Koen S. MD, PhD12; Egerod, Ingrid RN, PhD13; Burry, Lisa D. PharmD14,15; Beishuizen, Albertus MD, PhD16; Matos, Joaquim RN, BSc17; Donders, A. Rogier T. PhD18; Pickkers, Peter MD, PhD1,19; van den Boogaard, Mark RN, PhD1

doi: 10.1097/CCM.0000000000003911
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Objectives: To externally validate two delirium prediction models (early prediction model for ICU delirium and recalibrated prediction model for ICU delirium) using either the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist for delirium assessment.

Design: Prospective, multinational cohort study.

Setting: Eleven ICUs from seven countries in three continents.

Patients: Consecutive, delirium-free adults admitted to the ICU for greater than or equal to 6 hours in whom delirium could be reliably assessed.

Interventions: None.

Measurements and Main Results: The predictors included in each model were collected at the time of ICU admission (early prediction model for ICU delirium) or within 24 hours of ICU admission (recalibrated prediction model for ICU delirium). Delirium was assessed using the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist. Discrimination was determined using the area under the receiver operating characteristic curve. The predictive performance was determined for the Confusion Assessment Method-ICU and Intensive Care Delirium Screening Checklist cohort, and compared with both prediction models’ original reported performance. A total of 1,286 Confusion Assessment Method-ICU–assessed patients and 892 Intensive Care Delirium Screening Checklist–assessed patients were included. Compared with the area under the receiver operating characteristic curve of 0.75 (95% CI, 0.71–0.79) in the original study, the area under the receiver operating characteristic curve of the early prediction model for ICU delirium was 0.67 (95% CI, 0.64–0.71) for delirium as assessed using the Confusion Assessment Method-ICU and 0.70 (95% CI, 0.66–0.74) using the Intensive Care Delirium Screening Checklist. Compared with the original area under the receiver operating characteristic curve of 0.77 (95% CI, 0.74–0.79), the area under the receiver operating characteristic curve of the recalibrated prediction model for ICU delirium was 0.75 (95% CI, 0.72–0.78) for assessing delirium using the Confusion Assessment Method-ICU and 0.71 (95% CI, 0.67–0.75) using the Intensive Care Delirium Screening Checklist.

Conclusions: Both the early prediction model for ICU delirium and recalibrated prediction model for ICU delirium are externally validated using either the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist for delirium assessment. Per delirium prediction model, both assessment tools showed a similar moderate-to-good statistical performance. These results support the use of either the early prediction model for ICU delirium or recalibrated prediction model for ICU delirium in ICUs around the world regardless of whether delirium is evaluated with the Confusion Assessment Method-ICU or Intensive Care Delirium Screening Checklist.

1Department of Intensive Care Medicine, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

2Faculty of Health Sciences and National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (Wessex), University of Southampton, Southampton, United Kingdom.

3Scientific Institute for Quality of Healthcare, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

4School of Pharmacy, Northeastern University, Boston, MA.

5Division of Pulmonary, Critical Care and Sleep Medicine, Tufts Medical Center, Boston, MA.

6Intensive Care Unit, Department of Intensive Care Medicine, The Canberra Hospital, Canberra, ACT, Australia.

7Faculty of Health, University of Canberra, Canberra, ACT, Australia.

8College of Health and Medicine, Australian National University, Canberra, ACT, Australia.

9Department of Intensive Care Medicine and Brain Center Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands.

10Department of Critical Care Medicine, Antwerp University Hospital, University of Antwerp, Edegem (Antwerp), Belgium.

11Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands.

12Department of Intensive Care Medicine, Jeroen Bosch Ziekenhuis, ‘s-Hertogenbosch, The Netherlands.

13Intensive Care Unit, Department of Intensive Care Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.

14Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.

15Department of Pharmacy, Mount Sinai Hospital, Sinai Health System, Toronto, ON, Canada.

16Department of Intensive Care, Medisch Spectrum Twente, Enschede, The Netherlands.

17Department of Intensive Care Medicine, Hospital Espírito Santo, Evora, Portugal.

18Department for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

19Radboud Center for Infectious Diseases, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

This work was performed at the Radboud University Medical Center, Tufts Medical Center, The Canberra Hospital, Antwerp University Hospital, Erasmus Medical Center, Jeroen Bosch Ziekenhuis, Rigshospitalet, Mount Sinai Hospital, Medisch Spectrum Twente, Hospital Espírito Santo, and University Medical Centre Utrecht.

Drs. Wassenaar, Schoonhoven, Donders, Pickkers, and van den Boogaard contributed to study concept and design. Drs. Wassenaar, Devlin, and van Haren, Slooter, Jorens, van der Jagt, Simons, Egerod, Burry, and Beishuizen, and Mr. Matos contributed to acquisition of data. Drs. Wassenaar, Donders, and van den Boogaard contributed to statistical analysis. Drs. Wassenaar, Schoonhoven, Donders, Pickkers, and van den Boogaard contributed to analysis and interpretation of data. Dr. Wassenaar contributed to drafting of the article. Drs. Schoonhoven, Devlin, and van Haren, Slooter, Jorens, van der Jagt, Simons, Egerod, Burry, and Beishuizen, Mr. Matos, and Drs. Donders, Pickkers, and van den Boogaard contributed to critical revision of the article for important intellectual content. Drs. Schoonhoven, Pickkers, and van den Boogaard contributed to study supervision. All authors read and approved the final article.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal).

Dr. Pickkers received funding from AM-Pharma, Adrenomed, Exponential Biotherapies, and Baxter Consultation (speaking fee). The remaining authors have disclosed that they do not have any potential conflicts of interest.

For information regarding this article, E-mail: mark.vandenboogaard@radboudumc.nl

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